Predicting non-compliance in the Atlantic Canada lobster fisheryTools Graham, Scott (2012) Predicting non-compliance in the Atlantic Canada lobster fishery. PhD thesis, University of Nottingham.
AbstractThe overall research question originated through the question “how did the underground economy in the lobster fishery arise and why”. In the mid-1990s, a growing underground economy was uncovered by chance in the Atlantic Canada lobster fishery. When the Royal Canadian Mounted Police proceeds of crime unit found a series of large money transfers into a Royal Bank branch in Halifax, they thought that drug money was being moved. It turned out to have been cash sales of lobster. This represents $40 to $60 million in lost tax revenue, and a similar challenge for the common resource model for lobster fisheries management. To help answer the research question I examined the history and structure of the Atlantic Canadian lobster fishery, the impact of government and non-government policies and interactions with the lobster fishery and examined the tax evasion, statistical fraud detection and collusion/market power literature. The literature review gave rise to a number of potential variables for inclusion in a model that would serve to predict illegal and underreported activity in the lobster fishery. First, Benford’s Law was tested as a possible variable for inclusion. Non-conformity with Benford’s Law was observed in both the lobster fishery in LFA33 and LFA34 plus the snowcrab fishery. However, non conformance with Benford’s Law does not mean that there is certainty of fraud or human manipulation. Second, a market power screen was applied to the lobster fishery. Quantitative support for community-based differences in compliance with fisheries regulations has been demonstrated there is value in including a market power indicator variable as a variable of interest in the model. Last logistic panel data models were developed and tested. The outcome of the model building process were two models that have a better than chance discriminatory ability and a reasonable classification of transactions that may lead to sanctions. Model 4 was significant but was not able to classify licensees that were more likely to have sanctions. A factor analysis showed that there were three factors for each of the transactional and licensee models. For licensee models,sanctions were not loading on the same factor as the Benford’s Law and market power independent variables. In the case of the underground economy of the Atlantic Canadian lobster fishery, the Government of Canada has information and a fresh analysis of the information that may enable them to better target audits or inspections. There is no illusion that the information will, in sports parlance, “win the championship” however, it is hoped that with this analysis and continued improvement that the Government of Canada will outperform those that seek to evade tax and fisheries policy.
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